Title :
Fuzzy kernel discriminant analysis (FKDA) and its application to face recognition
Author :
Wu, Xiao-jun ; Gu, Li-min ; Wang, Shi-Tong ; Yang, Jing-Yu ; Zheng, Yu-jie ; Yu, Dong-jun
Author_Institution :
Southern Yangtze Univ., Wuxi
Abstract :
A fuzzy kernel diccriminant analysis algorithm (FKDA) is proposed in this paper, which is the kernel version of the fuzzy fisherface method. First, KPCA is performed on the training data. Then fuzzy k-nearest neighbor (FKNN) is introduced to find the mean vectors of each class. Fuzzy scatter matrices are derived for fuzzy LDA in the kernel space. The results of experiments conducted on ORL database show that the proposed method is better than fuzzy fisherface method in terms of accurate recognition rate.
Keywords :
face recognition; fuzzy set theory; ORL database; face recognition; fuzzy fisherface method; fuzzy k-nearest neighbor; fuzzy kernel discriminant analysis; fuzzy scatter matrices; Algorithm design and analysis; Face recognition; Humans; Information analysis; Kernel; Linear discriminant analysis; Pattern analysis; Pattern recognition; Scattering; Wavelet analysis; Fisherface; feature extraction; fuzzy k-nearest neighbor; kernel method;
Conference_Titel :
Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1065-1
Electronic_ISBN :
978-1-4244-1066-8
DOI :
10.1109/ICWAPR.2007.4420648
